Cellular telephone transmission has long been used in mobile communication. Traditionally, cellular telephone transmission has been used to facilitate conversations between remote individuals. More recently, these same systems have been modified to facilitate the communication of verbal instructions to remote computer systems using speech recognition programs. In these modified systems, the speaker's verbal instructions are converted to digital data instructions, which in turn are used by a computer system to carry out the desired operation. The ability to communicate verbal instructions “hands-free” carries obvious advantages, not the least of which include safety advantages, especially when the speaker is concurrently attempting to operate a vehicle.
The traditional implementation of this type of speech transmission and recognition occurs in one of two ways: (1) sending raw audio (i.e., the speaker's verbal instructions) from a receiver in the vehicle, such as a cellular telephone, to the remote computer system, where the verbal instructions are converted to data instructions; or (2) performing extensive automated speech recognition (ASR) in the receiver (e.g., recognizing words and phrases), and sending the converted digital data instructions to the remote computer system. Both existing implementations suffer from significant disadvantages. Raw audio sent across a cellular network suffers from signal degradation, in turn diminishing the integrity of the audio signal to be converted to digital data instructions and, hence, the accuracy of the ultimate instructions. While converting the audio signal to digital data at the vehicle addresses this problem, it requires expensive computing power in the vehicle, which is logistically and cost prohibitive.
Thus, there is a need for a mobile speech recognition system and method that addresses the disadvantages with the current implementations.